BCPPS Statistics -PEDS Complete exam Questions
with Correct Answers of the Latest Update
2024/2025
Two types of continuous variables & their descriptions - ✔✔1. interval--data ranked
in a specific order with a consistent change in magnitude between units, zero point is
arbitrary (degrees Fahrenheit)
2. Ratio--HAS an absolute zero (heart rate, blood pressure, time, distance, otherwise like
interval)
Median - ✔✔midpoint of values when placed in order from highest to lowest
Mode - ✔✔most common value in a description
Two parameters that define a normally distributed population (Gaussian) - ✔✔1.
mean
2. SD
95% CI calculation - ✔✔mean +/- (2*SEM)
CI's - ✔✔Help determine importance of findings, give an idea of magnitude of
difference between groups & the statistical significance
~a range data together w/a point estimate of the difference
What do p-values tell us? - ✔✔tell if statistically significant difference between
groups but they don't tell us anything about the magnitude of the difference
,CI that includes 0 - ✔✔means no difference between two variables, interpreted as
NOT statistically significant (a p-value of 0.05 or greater)
(No need to show both 95% CI & the p-value.)
Assumptions of parametric tests - ✔✔1. data have an underlying normal distribution
(estimate by mean~median)
2. continuous data (either interval or ratio)
3. data have variances that are homogeneous between the groups investigated
When to use Nonparametric test - ✔✔1. data aren't normally distributed
2. data don't meet other criteria for parametric tests (discrete data)
Parametric test for comparing sample with population mean - ✔✔Student t-test one-
sample
Nominal data test comparing expected & observed proportions between 2 or more
groups - ✔✔Chi-square (x2)
Nominal test when data is less than 5 predicted observations - ✔✔Fisher exact test
Nominal data paired samples test - ✔✔McNemar
Nominal data test controlling for the influence of confounders - ✔✔Mantel-Haenszel
Non parametric test for two independent samples - ✔✔Wilcoxon rank sum, Mann-
Whitney U, Wilcoxon Mann-whitney
, Non parametric test for 3 or more independent samples, - ✔✔Kruskal-Wallis one-way
ANOVA by ranks
Nonparametric test for two matched or paired samples - ✔✔Sign test & Wilcoxon
signed rank test
Non-parametric test for three or more matched or paired groups - ✔✔Friedman
ANOVA by ranks
Type II error (beta error) - ✔✔false negative
p-value - ✔✔calculation that a Type I error has occurred
Pearson correlation - ✔✔strength of relationship between 2 variables (r ranges -1 - 1)
Power - ✔✔ability to detect differences between groups if one actually exists (1-
Beta)
Sensitivity - ✔✔proportion of patients w/disease who have a positive test (percent of
true positives)
Specificity - ✔✔proportion of patients without disease who have a negative test
(percent of true negatives)
calculation of sensitivity - ✔✔True positives divided by False negatives + True
positives (A/(A+C))
(TP/(FN + TP))
with Correct Answers of the Latest Update
2024/2025
Two types of continuous variables & their descriptions - ✔✔1. interval--data ranked
in a specific order with a consistent change in magnitude between units, zero point is
arbitrary (degrees Fahrenheit)
2. Ratio--HAS an absolute zero (heart rate, blood pressure, time, distance, otherwise like
interval)
Median - ✔✔midpoint of values when placed in order from highest to lowest
Mode - ✔✔most common value in a description
Two parameters that define a normally distributed population (Gaussian) - ✔✔1.
mean
2. SD
95% CI calculation - ✔✔mean +/- (2*SEM)
CI's - ✔✔Help determine importance of findings, give an idea of magnitude of
difference between groups & the statistical significance
~a range data together w/a point estimate of the difference
What do p-values tell us? - ✔✔tell if statistically significant difference between
groups but they don't tell us anything about the magnitude of the difference
,CI that includes 0 - ✔✔means no difference between two variables, interpreted as
NOT statistically significant (a p-value of 0.05 or greater)
(No need to show both 95% CI & the p-value.)
Assumptions of parametric tests - ✔✔1. data have an underlying normal distribution
(estimate by mean~median)
2. continuous data (either interval or ratio)
3. data have variances that are homogeneous between the groups investigated
When to use Nonparametric test - ✔✔1. data aren't normally distributed
2. data don't meet other criteria for parametric tests (discrete data)
Parametric test for comparing sample with population mean - ✔✔Student t-test one-
sample
Nominal data test comparing expected & observed proportions between 2 or more
groups - ✔✔Chi-square (x2)
Nominal test when data is less than 5 predicted observations - ✔✔Fisher exact test
Nominal data paired samples test - ✔✔McNemar
Nominal data test controlling for the influence of confounders - ✔✔Mantel-Haenszel
Non parametric test for two independent samples - ✔✔Wilcoxon rank sum, Mann-
Whitney U, Wilcoxon Mann-whitney
, Non parametric test for 3 or more independent samples, - ✔✔Kruskal-Wallis one-way
ANOVA by ranks
Nonparametric test for two matched or paired samples - ✔✔Sign test & Wilcoxon
signed rank test
Non-parametric test for three or more matched or paired groups - ✔✔Friedman
ANOVA by ranks
Type II error (beta error) - ✔✔false negative
p-value - ✔✔calculation that a Type I error has occurred
Pearson correlation - ✔✔strength of relationship between 2 variables (r ranges -1 - 1)
Power - ✔✔ability to detect differences between groups if one actually exists (1-
Beta)
Sensitivity - ✔✔proportion of patients w/disease who have a positive test (percent of
true positives)
Specificity - ✔✔proportion of patients without disease who have a negative test
(percent of true negatives)
calculation of sensitivity - ✔✔True positives divided by False negatives + True
positives (A/(A+C))
(TP/(FN + TP))
